saa.neighborhood1

An instance of ObjectiveFunction (or subclass) class <a rd-options="" href="/link/ObjectiveFunction?package=evoper&version=0.5.0" data-mini-rdoc="evoper::ObjectiveFunction">ObjectiveFunction</a>

The current solution to find a neighbor

The distance from current solution S <code>distance = (max - min) * d</code>

Generates neighbor solutions perturbing one parameter from current
solution <code>S</code> picked randonly.

The EvoPER, Evolutionary Parameter Estimation for Individual-based Models is an extensible
package providing optimization driven parameter estimation methods using metaheuristics and
evolutionary computation techniques (Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization
for continuous domains, Tabu Search, Evolutionary Strategies, ...) which could be more efficient and require,
in some cases, fewer model evaluations than alternatives relying on experimental design. Currently there
are built in support for models developed with 'Repast Simphony' Agent-Based framework (<https://repast.github.io/>)
and with NetLogo (<https://ccl.northwestern.edu/netlogo/>) which are the most used frameworks for Agent-based modeling.

Antonio Prestes Garcia

evoper

Evolutionary Parameter Estimation for 'Repast Simphony' Models

Alfonso  Rodriguez-Paton

saa.neighborhood1 function

<dl><dt>f</dt>
<dd>An instance of ObjectiveFunction (or subclass) class ObjectiveFunction</dd>
<dt>S</dt>
<dd>The current solution to find a neighbor</dd>
<dt>d</dt>
<dd>The distance from current solution S <code>distance = (max - min) * d</code></dd></dl>

Arguments

saa.neighborhood1 — saa.neighborhood1

<dl>

<dt>f</dt>
<dd>An instance of ObjectiveFunction (or subclass) class ObjectiveFunction</dd>


<dt>S</dt>
<dd>The current solution to find a neighbor</dd>


<dt>d</dt>
<dd>The distance from current solution S <code>distance = (max - min) * d</code></dd>

</dl>

saa.neighborhood1: saa.neighborhood1

Description

Usage

Value

Arguments